Looks like it may be related to
https://issues.apache.org/jira/browse/SPARK-3807.
I will build from branch 1.1 to see if the issue is resolved.
Chen
On Tue, Oct 14, 2014 at 10:33 AM, Chen Song <chen.song...@gmail.com> wrote:
> Sorry for bringing this out again, as I have no clue what could have
> caused this.
>
> I turned on DEBUG logging and did see the jar containing the SerDe class
> was scanned.
>
> More interestingly, I saw the same exception
> (org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
> attributes) when running simple select on valid column names and malformed
> column names. This lead me to suspect that syntactical breaks somewhere.
>
> select [valid_column] from table limit 5;
> select [malformed_typo_column] from table limit 5;
>
>
> On Mon, Oct 13, 2014 at 6:04 PM, Chen Song <chen.song...@gmail.com> wrote:
>
>> In Hive, the table was created with custom SerDe, in the following way.
>>
>> row format serde "abc.ProtobufSerDe"
>>
>> with serdeproperties ("serialization.class"=
>> "abc.protobuf.generated.LogA$log_a")
>>
>> When I start spark-sql shell, I always got the following exception, even
>> for a simple query.
>>
>> select user from log_a limit 25;
>>
>> I can desc the table without any problem. When I explain the query, I got
>> the same exception.
>>
>>
>> 14/10/13 22:01:13 INFO impl.AMRMClientImpl: Waiting for application to be
>> successfully unregistered.
>>
>> Exception in thread "Driver" java.lang.reflect.InvocationTargetException
>>
>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>
>> at
>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>
>> at
>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>
>> at java.lang.reflect.Method.invoke(Method.java:606)
>>
>> at
>> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:162)
>>
>> Caused by:
>> org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
>> attributes: 'user, tree:
>>
>> Project ['user]
>>
>> Filter (dh#4 = 2014-10-13 05)
>>
>> LowerCaseSchema
>>
>> MetastoreRelation test, log_a, None
>>
>>
>> at
>> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$$anonfun$apply$1.applyOrElse(Analyzer.scala:72)
>>
>> at
>> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$$anonfun$apply$1.applyOrElse(Analyzer.scala:70)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:165)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:183)
>>
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>>
>> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
>>
>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>>
>> at
>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
>>
>> at
>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
>>
>> at
>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
>>
>> at scala.collection.TraversableOnce$class.to
>> (TraversableOnce.scala:273)
>>
>> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
>>
>> at
>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
>>
>> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
>>
>> at
>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
>>
>> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:212)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:168)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:156)
>>
>> at
>> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$.apply(Analyzer.scala:70)
>>
>> at
>> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$.apply(Analyzer.scala:68)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:60)
>>
>> at
>> scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:34)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51)
>>
>> at scala.collection.immutable.List.foreach(List.scala:318)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51)
>>
>> at
>> org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:397)
>>
>> at
>> org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:397)
>>
>> at
>> org.apache.spark.sql.hive.HiveContext$QueryExecution.optimizedPlan$lzycompute(HiveContext.scala:358)
>>
>> at
>> org.apache.spark.sql.hive.HiveContext$QueryExecution.optimizedPlan(HiveContext.scala:357)
>>
>> at
>> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:402)
>>
>> at
>> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:400)
>>
>> at
>> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:406)
>>
>> at
>> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:406)
>>
>> at org.apache.spark.sql.SchemaRDD.collect(SchemaRDD.scala:438)
>>
>> at com.appnexus.data.spark.sql.Test$.main(Test.scala:23)
>>
>> at com.appnexus.data.spark.sql.Test.main(Test.scala)
>>
>> ... 5 more
>>
>>
>> --
>> Chen Song
>>
>>
>
>
> --
> Chen Song
>
>
--
Chen Song
